Enterprise Big Data Architecture



Data is an integral part of the enterprise.

Insights generated from data provides repeated, lasting value to the business to service its end goals. A prerequisite though is to have enterprise architecture in place to host and provide the data to every stakeholder. This is achieved through purposeful design, whereas the typical organization tends to approach IT architecture organically.

With the recent explosive growth in data volumes and the vast variety in which enterprise data is collected, the design of the data architecture can itself be a challenge. Add to the mix the complexities arising from the quickly-evolving big data software industry with vendors and open-source software providers dishing out new improvements at such a rapid pace that at times capabilities and even entire tools are rendered irrelevant or redundant.

Our Enterprise Big Data Architecture service is offered to those customers who are well down the path of using data to further their business and now want to explore how big data frameworks and methodologies can be incorporated into their core architecture.

The service starts with an assessment of the ‘As-Is Situation’, including the data collected, the types of uses, the motivating business questions, and the tools involved. This is immediately followed by the collaborative exercise of identifying those needs not being serviced satisfactorily in the ‘As-Is Architecture. A crucial deliverable of this second step is the identification of the set of business-driven use cases that can best be serviced by incorporating big data into the core enterprise architecture, referred to as the ‘To-Be Architecture’.

In the final step, we provide you the technology options to consider in implementing the To-Be Architecture along with a detailed discussion of the merits and demerits of each and every option. Typical decision factors used in tool comparisons are customized to the enterprise context keeping in mind the new business use cases too.

As an optional addendum to the service, we can also help the enterprise in the technical evaluation of chosen tools and quantitatively illustrate their appropriate placement in the To- Be Architecture.

Our Industry View

Apache Nifi Overview and Comparison Study

Apache Nifi is a recent addition to the family of distributed data processing frameworks. Nifi provides a reliable, UI based mechanism to transport, filter and enrich data across multiple systems. What are some of the unique features of Nifi and how well does Nifi weigh out, in comparison to or in complement to the other data transfer/processing frameworks like Flume,Kakfa, etc?

Guaranteeing exactly-once load semantics in moving data from Kafka to HDFS

Kafka has become a center piece in modern enterprise data architectures. Hadoop serving the role of persistent historical store that supports a myriad of workloads. Moving data from Kafka to Hadoop is a common task in such architectures. Read to find out more about the considerations and how to realize critical data pipelines.